Search Results (563)

This study addresses the critical importance of fire safety considerations during the design phase of commercial buildings, particularly in Saudi Arabia, where urbanization and climate-specific risks pose unique challenges. Recognizing that high-risk structures often experience fire-related incidents due to inadequate safety measures, this research develops a comprehensive framework to guide design professionals in integrating effective fire safety strategies. Using a mixed-methods approach, the study combined a literature review, qualitative expert interviews, and a questionnaire survey. The final quantitative analysis was based on 86 valid survey responses, including 29 authority or regulation implementers, 28 designers, and 29 stakeholders. The survey results highlighted significant gaps in knowledge and implementation, particularly among stakeholders. Key challenges identified included cultural attitudes toward safety, lack of training, and inadequate use of fire-resistant materials. The framework proposes a structured methodology for enhancing fire safety measures across the design stages, emphasizing the importance of collaboration among architects, engineers, safety consultants, and regulatory bodies. Recommendations include regular updates to fire safety documents, fostering a culture of safety awareness, and conducting post-occupancy evaluations to assess the effectiveness of implemented measures. Ultimately, this research aims to benefit various stakeholders, including design professionals and regulatory agencies, by promoting a proactive approach to fire safety that enhances building resilience and protects lives and property in commercial environments. Full article

Leakage incidents at natural gas distribution stations (NGDSs) present severe fire and explosion risks, demanding immediate, data-driven emergency responses. While crucial for minimizing hazard impacts, real-time prediction of gas dispersion ranges remains a significant operational challenge. To partially address this critical safety need, this study introduces a rapid-response prediction framework prototype integrating computational fluid dynamics (CFD) with machine learning (ML). Specifically, a comprehensive database of 500 experimentally validated CFD leakage scenarios at 60 s was developed first, specifically focusing on mapping gas concentration contours within the critical 5–15% flammability range. To identify the most effective real-time predictive tool, three ML algorithms, including a backpropagation neural network (BPNN), long short-term memory (LSTM), and gated recurrent unit (GRU), were evaluated. The BPNN initially outperformed the sequence models, with a coefficient of determination (R²) of 0.96, a mean squared error (MSE) of 1.35, a mean absolute error (MAE) of 0.77, a maximum absolute error (MaxAE) of 4.94 and an average training time of 4.23 s per epoch. To further meet the stringent speed and precision demands of emergency scenarios, the model was enhanced via particle swarm optimization (PSO-BPNN). This optimized framework achieved exceptional accuracy (R² = 0.99, MSE = 0.34, and MAE = 0.38) while reducing the training time to just 1.42 s per epoch under the current computational configuration. The developed CFD-ML prototype provides a practical, highly efficient tool for NGDS operators and emergency responders, enabling them to instantly visualize hazard zones, optimize evacuation protocols, and safely mitigate leakage incidents before ignition occurs. Full article

Wildfires are significant and increasing hazards in the United Kingdom (UK), affecting both ecosystem integrity and public safety, particularly within many rural–urban interface locations. In moorland environments, where recreational pressure is high, human negligence often remains a major ignition source. The Peak District National Park in Central England is vulnerable to these hazards, as exemplified by the 2018 wildfire at The Roaches Nature Reserve, which was triggered by an out-of-control barbecue. Despite increasing wildfire risk due to climate change, public awareness and perceptions of wildfire impact in the UK are limited. This study used an online questionnaire survey to examine public understanding of wildfires among a non-specialist audience and how the ‘2018 Roaches wildfire’ influenced Reserve users’ perceptions of impacts, recovery, and management. Respondents demonstrated a general awareness of wildfire severity, ignition sources, and global fire geography, although familiarity with specific UK incidents varied. Perceptions of impacts were mixed, reflecting different experiences and emotional responses to the 2018 event. Ecological aspects, such as soil, biodiversity, and landscape aesthetics, were widely perceived as ‘slow to recover’, whereas recreation, safety, and health were viewed as returning to normal more quickly. A strong sense of shared responsibility for wildfire safety emerged, with participants emphasizing the need for clearer communication, improved public education, and higher levels of community involvement. These findings provide exploratory but valuable insights into public perceptions of UK wildfires, thereby informing future research pathways to strengthen fire management and preparedness. Full article

As key units in China’s new urbanization process, municipal districts exhibit distinct fire risk characteristics due to dense populations, concentrated infrastructure, and intensive socio-economic activities. Taking Xiaoshan District as an illustrative case of a highly urbanized and industrialized municipal district, this study analyzes fire incidents from 2020 to 2023 from temporal, spatial, and causal perspectives. During the study period, 5011 fire incidents were recorded, resulting in 3 deaths, 2 injuries, and direct property loss of 73.41 million CNY. The results indicate that highly urbanized and industrialized districts such as Xiaoshan may simultaneously face frequent fire occurrence pressure, relatively low casualty levels, and strong sensitivity to large-loss incidents. Temporally, fire occurrence was strongly coupled with human activity patterns rather than being dominated solely by seasonal factors. The period from 4 p.m. to 8 p.m. accounted for 32.47% of daily fire incidents, whereas only 9.10% occurred between 2 a.m. and 6 a.m.; however, early morning fires were associated with more serious property loss. Spatially, resident population and industrial output value above designated size were identified as the primary socio-economic factors associated with the spatial differentiation of fire incidents and direct property loss at the town/subdistrict scale. In terms of causation, electrical issues were the leading cause of fire incidents, accounting for 31.95% of fires and 32.92% of direct property loss. In addition, direct property loss attributed to “other” causes was disproportionately high, highlighting the need to improve the professionalism, granularity, and consistency of fire cause investigation. These findings provide case-based empirical evidence for refined fire prevention, electrical fire control, early warning, and targeted fire safety management in highly urbanized and industrialized districts with similar development conditions. Full article

Dust and coal mine gas in deep mines are highly prone to causing fires, and the cyclic high temperatures generated by such fires are one of the key factors contributing to the instability of deep rock structures. To research the dynamic splitting tensile mechanical properties of sandstone subjected to high-temperature cycling, impact splitting tensile tests were performed on sandstone specimens under normal temperature and after high-temperature cycling treatments ranging from 250 °C to 900 °C using a split Hopkinson pressure bar (SHPB) with increasing cyclic temperature. The average dynamic tensile strength of sandstone specimens declines following a quadratic function, dropping from 18.07 MPa at T = 150 °C to a minimum value of 3.08 MPa, representing a maximum reduction of 82.96%. The dynamic strain and average strain rate exhibit increasing trends following exponential and logarithmic functions, respectively, while the dynamic elastic modulus exhibits a logarithmic declining trend. As the cyclic temperature grows, the degree of fragmentation of the specimens intensifies, transitioning from axial splitting failure to pulverization failure, with fragment size decreasing and fractal dimension exhibiting increasing trends. For temperatures between 450 °C and 600 °C, the dynamic tensile strength, dynamic strain, average strain rate, dynamic elastic modulus, average particle size, and fractal dimension all show a distinct interval behavior. As the cyclic temperature rises, the incident, reflected, and transmitted energies gradually decline. A higher fragmentation energy density corresponds to more severe specimen fragmentation, and the average fragment size follows a negative quadratic relationship with fragmentation energy density, which effectively quantifies the dynamic splitting tensile fragmentation behavior of rock. The findings of this study regarding the dynamic behavior and damage evolution of sandstone under cyclic high-temperature conditions can serve as a reference for assessing rock mass stability in high-temperature applications such as underground engineering and resource development. Full article

Urban fire incidents in complex built environments pose severe threats to public safety. However, the unstructured nature of urban scenes presents substantial challenges for existing detection algorithms in reliably identifying incipient flames and diffuse smoke under dynamic visual interference. To address this issue, we propose YOLO-Fire, a lightweight and high-precision detection algorithm based on YOLOv11. Specifically, a Hybrid Feature Fusion Module (HFFM) adopts a parallel dual-stream architecture to structurally decouple high-frequency flame boundaries from low-frequency smoke textures. A Dual-Scale Contextual Diffusion (DCD) mechanism establishes global contextual constraints through an additive diffusion strategy, effectively suppressing fire-like background interference while enhancing semi-transparent smoke features. In addition, a Gaussian Spatial Pyramid Pooling Fast (GSPPF) module further improves multi-scale receptive field aggregation. Evaluated on a self-constructed large-scale urban fire dataset, YOLO-Fire achieves an mAP50 of 75.7%, mAP50-95 of 53.3%, and an F1-score of 73.7%, with only 10.02 M parameters, surpassing the YOLOv11 baseline by 2.4%, 4.5%, and 2.9%, respectively. Ablation studies confirm that each proposed module contributes both independently and synergistically to the overall performance gains. Comprehensive comparisons with mainstream detectors and specialized fire detection models further demonstrate that YOLO-Fire achieves superior overall performance, outperforming YOLO-FireAD and FireSmoke-YOLO by 2.7% and 2.4% in mAP50, respectively, while maintaining lower computational complexity. Furthermore, inference evaluation on a single-core CPU achieves 17.28 FPS, validating the practical deployment potential of YOLO-Fire in resource-constrained environments and offering an efficient, lightweight solution for real-time urban fire surveillance and early warning. Full article

Building fires involve numerous interacting hazard factors, making it difficult to identify which combinations are most likely to cause an incident and to design targeted interventions. Existing methods address only part of this problem: structural approaches map causal pathways but cannot quantify the probability of specific factor combinations, while probabilistic models compute risk values but offer little guidance on where to intervene. To bridge this gap, we develop the Causal Hierarchy Model (CHM), a data-driven framework that integrates causal structure analysis with probability calculation. Factor influence is derived from empirical co-occurrence data to distinguish driving factors from dependent ones. A hierarchical structure is then constructed using two layering rules, revealing causal transmission gradients and critical hub nodes. Finally, coupling probabilities are computed within the hierarchical constraints and weighted by the influence of hubs. Applying CHM to building fire records from California reveals clear functional differentiation among hazard factors. Coupling strength attenuates asymmetrically across hierarchy levels but amplifies sharply along pathways that pass through high-prominence hubs. By uniting structure and probability, CHM provides a quantitative basis for shifting fire safety management from uniform inspection toward risk-differentiated strategies. Full article

The widespread adoption of photovoltaic systems in residential electrical installations has increased the importance of Automatic Transfer Switches (ATSs) for ensuring power continuity during grid outages. However, many low-cost ATS solutions available on the market prioritize economic efficiency over operational safety, leading to significant risks under fault conditions. This paper investigates a real overvoltage incident in a residential three-phase installation equipped with a photovoltaic inverter and an ATS, which resulted in the failure of multiple electronic loads. The study reconstructs the event and demonstrates that the loss of the neutral conductor during backup operation caused severe phase voltage imbalance, generating overvoltage conditions across lightly loaded phases. A simplified electrical model is used to explain current paths and voltage redistribution under asymmetric loads, highlighting the critical role of correct neutral switching in ATS design. Two commercially available ATS architectures, one based on a changeover-contact mechanism and one employing four-pole miniature circuit breakers, are experimentally evaluated. The evaluation reveals major design deficiencies, including the absence of protective elements for control circuits, reliance on mechanical end-position limiters, and the use of switching devices not intended for frequent source transfer. These shortcomings introduce risks such as uncontrolled actuator operation, overheating, mechanical damage, and potential fire hazards. To overcome these limitations, a new ATS architecture was developed using a phase-monitoring relay, interlocked ABB contactors, and dedicated fuse protection for all control circuits. Detailed laboratory measurements were conducted to characterize contactor switching times and internal relay command delays. By optimizing the command sequence, the proposed ATS achieves predictable, fault-tolerant operation with competitive transfer times, representing a meaningful safety improvement over the evaluated commercial alternatives. The proposed solution is scoped to three-phase residential installations equipped with a hybrid photovoltaic inverter providing a dedicated backup output, operating within TN-S or TN-C-S earthing systems with a maximum grid connection capacity of 21 kW. Full article

In recent years, global climate change has significantly increased the incidences of grassland fires, shifting their occurrence from seasonal events (primarily spring and autumn) to annual incidents. To enable a more accurate evaluation and zoning of grassland fire risk, this study established the Fire Source Hazard Index, Fire Fuel Hazard Index, and Fire Environmental Hazard Index based on multi-source data, employing the entropy weight method, random forest modeling, mathematical statistics, and spatial analysis. A comprehensive seasonal grassland fire hazard assessment model was constructed using these three indices and seasonal fire hazard zones were evaluated in Inner Mongolia. The results indicated that, among the fire source factors, the hazard weight of foreign fire sources was relatively high during spring (0.37) and summer (0.44). In autumn and winter, the hazard weights of road networks were higher, at 0.38 and 0.44, respectively. In the comprehensive hazard assessment, the fire environment hazard exhibited an objective existence with notable seasonal variation, whereas the hazard weight of fire source factors exceeded that of fuels across all seasons. The comprehensive grassland fire hazard in Inner Mongolia demonstrated distinct seasonality and regional heterogeneity. Temporally, fire hazards are widespread and intense in spring, limited and concentrated in summer, extensive yet dispersed in autumn, and lowest in winter. Spatially, grassland fire hazards decreased from east to west, with higher hazards concentrated in the eastern regions. Western Inner Mongolia had the lowest probability of fire occurrence. The validation results revealed a positive correlation between the proportion of fire points and hazard grades, confirming the rationality of the hazard classification and the accuracy of the assessment, which provides an important theoretical basis for the scientific management and effective prevention and control of grassland fires. Future research should further refine and explore more precise methods for grassland fire hazard assessment. Full article

Urban fire risk in high-density cities is characterized by complex spatial heterogeneity and nonlinear relationships with the built environment, population distribution, and climatic conditions. However, most existing studies rely on linear assumptions and offer limited interpretability. To address this gap, we developed an interpretable analytical framework that integrates the CatBoost model with SHAP (SHapley Additive exPlanations), using Futian District in Shenzhen as a case study. We constructed a fire risk surface from historical fire incident data using kernel density estimation (KDE) and incorporated multiple urban environmental factors—including points of interest (POIs), road networks, and meteorological variables—as explanatory variables. The CatBoost model captured nonlinear relationships, while SHAP quantified feature importance and revealed interaction effects. The results show that urban fire risk is strongly associated with the spatial agglomeration of population-related facilities, especially high-density commercial and residential areas, as well as thermal conditions. Several variables exhibit clear nonlinear threshold effects, with their influence on fire risk varying markedly across different intensity ranges. Interaction analysis further indicates that combinations of built-environment characteristics and climatic factors jointly shape the spatial pattern of fire risk. These findings provide empirical insights into the spatial mechanisms underlying urban fire risk and highlight the value of interpretable machine learning in urban safety research. The proposed framework offers a practical tool for developing more targeted, evidence-based fire risk management strategies in high-density urban areas. Full article

This study investigates the organic chemical content and ecological impact of firefighting runoff collected from real-world fire scenarios. To establish a direct link between chemical composition and environmental hazard, a comprehensive analytical framework was employed, integrating molecular fingerprinting via gas chromatography–tandem mass spectrometry (GC-MS/MS) with a multi-trophic battery of bioassays, including Aliivibrio fischeri, Heterocypris incongruens, and Sinapis alba L. The chemical characterization revealed highly heterogeneous profiles dominated by esters (up to 41%), alcohols (up to 25%), and phenols (up to 22%). A unique molecular marker, nitriles (15.9%), was identified in tire-related fire effluents, which corresponded with potent metabolic suppression in the Toxi-ChromoTest™. Ecotoxicological results demonstrated that most effluents reached Class IV (high acute toxicity), with universal 100% lethality observed in samples from large-scale incidents. Furthermore, a significant stimulatory effect was detected in S. alba (growth stimulation up to 12%) for scenarios involving polyurethane foam, illustrating the selective toxicity of specific molecular groups. Beyond ecological degradation, the high phenolic and nitrile loads identified across multiple scenarios represent a substantial public health risk, as these persistent contaminants can infiltrate groundwater, bypass conventional water treatment, and bioaccumulate in the human food chain. The findings suggest that the synergistic effect of hydrophobic xenobiotics and firefighting foams poses a severe threat to both aquatic biodiversity and human chemical safety. This research emphasizes that linking molecular fingerprinting with multi-level bioindicators is essential for a holistic risk assessment of firefighting operations. Full article

Obstacles can significantly affect the thermal radiation distribution of oil storage tank fires; however, this issue has received relatively limited attention in previous studies. Taking aviation kerosene fires as an example, this study employed a cylindrical flame radiation model combined with the Monte Carlo method to investigate the variation in the radiative flux incident on the target and the flame-target view factor under different obstacle widths (W), heights (H) and target distances (d). The results indicate that obstacles block the flame radiation path, thereby reducing the radiative flux in the region behind the obstacle compared with the unobstructed condition. The view factor first decreases with increasing W and then approaches a stable value. The critical width (W_cr) is independent of H but increases with d. A similar relationship is observed between H and the critical height (H_cr). Based on geometric analysis, analytical expressions for W_cr and H_cr were derived. In addition, a predictive model for the view factor shielding ratio (φ) was established using three dimensionless geometric parameters, achieving a coefficient of determination of R² = 0.976, which demonstrates good predictive accuracy. These findings provide theoretical guidance for fire risk assessment in tank farm areas. Full article

This systematic review examines the effect of pre-incident information on public preparedness prior to an emergency or disaster. Preparing members of the public for adverse events can improve self-sufficiency and improve health outcomes, particularly during periods when emergency responders are not immediately available. Twenty-three studies were identified, addressing both natural and human-influenced events. All the studies investigated pre-incident training targeting members of the public rather than specialist responders. The synthesis considered training content, delivery approaches and evaluation methods. The studies included preparation, personal safety, triage, first aid and evacuation in scenarios involving terrorism, fire, earthquake, flood and CBRN events. Pre-incident education generally improves knowledge and intention to act, with higher-intensity and interactive training yielding greater engagement and response. Due to the difficulty of simulating emergencies and disasters, several studies used self-reporting and hypothetical testing, while others attempted to create real-life scenarios. The immediate effects of pre-incident education were generally positive, although many studies tested outcomes theoretically or within a classroom environment. It was also noted that few studies considered retention over the medium to long term; this is a concern as temporal decay may reduce preparedness. This review provides a basis for continued development of public-facing pre-incident education to increase resilience to both terrorist attacks and natural disasters. Full article

Fire incidents in municipal waste management facilities remain a persistent safety issue, complicated by high variability and limited reliability of available data. This study presents a process-oriented evaluation of 86 fire incidents recorded between 2013 and 2022 in the South Moravian Region of the Czech Republic, based on a verified non-public database of the Fire Rescue Service. Most incidents (approximately 76%) were associated with municipal solid waste landfills, confirming their dominant role within the sector. Spontaneous combustion was identified as the most frequent ignition mechanism; however, in nearly 78% of cases, the exact cause could not be conclusively determined, indicating a high level of uncertainty in incident reporting. Key quantitative indicators, including extinguishing water consumption (mean 32 m³, median 10 m³) and affected fire area, exhibited substantial variability, limiting their direct use for quantitative evaluation. To address these limitations, representative fire scenarios were systematically identified and analysed using the ARIA 3 framework in combination with the Bow-Tie methodology. This approach enables the interpretation of fire incidents as disturbances in operational processes and supports the identification of scenario-specific preventive and mitigation barriers. The results show that, despite data uncertainty, incident records provide a robust basis for identifying recurring fire patterns and facility-specific vulnerabilities, supporting scenario-based risk management and informed decision-making in municipal waste management systems. Full article

Data centers are critical digital infrastructure supporting cloud computing, artificial intelligence, and global information services. Despite their high-reliability design, they remain vulnerable to fire incidents due to continuous operation, high electrical loads, dense power systems, and the increasing use of lithium-ion batteries. Although such events are rare, their consequences can be severe, including service disruption, equipment damage, financial loss, and risks to data integrity. This study presents a systematic literature review of fire safety risk management frameworks in data centers, following PRISMA guidelines. Peer-reviewed studies published between 2020 and 2025 were retrieved from Scopus and Web of Science, screened, and appraised using structured quality criteria. Twelve empirical studies were synthesized and benchmarked against NFPA 75 and NFPA 76 standards. The findings are organized into three domains: Strategic Management, Fire Risk, and Fire Preparedness. The results show a strong focus on technical prevention and electrical hazards, while organizational readiness, emergency response, and recovery remain underexplored. Benchmarking indicates that industry standards adopt a more comprehensive lifecycle approach than the academic literature. This study reframes data center fire safety as a socio-technical reliability system and highlights critical gaps, providing a foundation for future research and improved fire safety governance and resilience. Full article